3
University of Wuerzburg, Department of Bioinformatics, Biocenter, Germany

4
University of Wuerzburg, Department of Neurobiology and Genetics, Biocenter, Germany

We have proposed a new computational, Bioinformatics solution i.e. GenomeVX, towards the field of Genomics and Nucleic acid research. GenomeVX helps in understanding the Genome-wide comparative analyses of different human populations, as well as between species, focusing on the association studies relating genetic variation to disease with evidence of mutations. GenomeVX extracts data from the fields in VCF file (generated by the 1000 Genome Browser (1000 Genomes Project Consortium, et al., 2010)) and displays alleles for the substitutions and variations (SNP).
The graphical interface of the GenomeVX is very simple to install and use. It is a desktop application, which offers two integrated modules: VCF File Editor and VCF Extracted & Converted Information. Using these modules, user can load the VCF files in to the GenomeVX and can extract, parse and convert the nucleotides’ complex respective numbers to the representative notations (e.g. ACTG). Furthermore, it helps the user to convert analysed data in to the Microsoft Excel Sheets for better analysis, statistical visualization and sharing. The overall workflow and wiring of the components of the GenomeVX is presented in Figure 1.
GenomeVX implementation follows the principles of our newly proposed software engineering paradigm i.e. Butterfly (Ahmed et al., 2014a; Ahmed and Zeeshan, 2014b). It is programmed in C# programming language, using Microsoft Visual Studio Dot Net Framework and only compatible to the Microsoft Windows Operating Systems (preferred OS version: 7). Most recent available version of the GenomeVX is in testing and in limited use, and we are focusing on the future research and development objectives by enhancing the its capabilities with more features.
The six steps installation process of GenomeVX is presented in the Figure 2 and it is freely available for any non-commercial, academic and scientific use at the following web link: (https://zenodo.org/record/13815?ln=en#.VOZSxC6ZNS0).

Figure 1

Figure 2

Acknowledgements

Funding: The authors would like to thank German Research Foundation (DFG-CRC-SFB-1047 to ZA, NP and DFG-CRC-TR34/Z1 to SZ, TD) for funding on this research.

Support: The authors thank to the University of Wuerzburg Germany, University of Massachusetts USA and The Jackson Laboratory for Genomic Medicine USA for support in this publication. Authors also thank to all interested colleagues for critical input on the approach and anonymous reviewers for helpful comments.